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Changelog

Source: NEWS.md

multimput 0.2.14

  • In case all imputed values are identical, model_impute() only runs a single model on one imputation. It reports the mean and standard errors based on the single model as-is.
  • model_impute() handles empty data.
  • model_impute() can filter the covariates with a user supplied function.
  • model_impute() gains a timeout argument.
  • Bugfix in generating zero-inflated negative binomial data.

multimput 0.2.13

  • aggregate_impute() handles the corner case when join results in an empty dataset.
  • The model_fun argument of model_impute() can be either a function or a string containing the name of a function (like "glm"). Include the package name in case the function is not available in base R (like "INLA::inla").

multimput 0.2.12

  • impute() gains an extra argument. Use it for observations not in the model that you still want to add in the follow-up analysis. For example: exclude rare observations from the model but you want them in the aggregations.
  • impute() on INLA models now also handles the binomial, the zero-inflated Poison (type 0 and 1) and the zero-inflated negative binomial (type 0 and 1) distributions.
  • Add hurdle_impute() to fit a hurdle model based on a model of the presences and a model of the counts.
  • Added validation rules for rawImputed and aggregatedImputed objects.
  • Update checklist infrastructure.

multimput 0.2.11

multimput 0.2.10

multimput 0.2.7.9000